Cloud computing is an emerging technological solution widely used in many fields. Initially developed as a
flexible way of managing peak demand it has began to make its way in scientific research.
One of the greatest advantages of cloud computing for scientific research is independence of having access
to a large cyberinfrastructure to fund or perform a research project. Cloud computing can avoid maintenance
expenses for large supercomputers and has the potential to ’democratize’ the access to high-performance comput-
ing, giving flexibility to funding bodies for allocating budgets for the computational costs associated with a project.
Two of the most challenging problems in atmospheric sciences are computational cost and uncertainty in
meteorological forecasting and climate projections. Both problems are closely related. Usually uncertainty can
be reduced with the availability of computational resources to better reproduce a phenomenon or to perform a
larger number of experiments. Here we expose results of the application of cloud computing resources for climate
modeling using cloud computing infrastructures of three major vendors and two climate models. We show how
the cloud infrastructure compares in performance to traditional supercomputers and how it provides the capability
to complete experiments in shorter periods of time. The monetary cost associated is also analyzed. Finally we
discuss the future potential of this technology for meteorological and climatological applications, both from the
point of view of operational use and research.
Keywords: atmospheric sciences, cloud computing